KNN search two arrays with 2000 elements












1















What I did:




  1. installed postgresql 9.3.1

  2. installed postgis 2.1.2

  3. I tried to find the distance by selecting column input_variable_1 with value 50.


I got the following result.



select input_variable_1 <-> 50  as distance  from test_ata limit 10;
distance
48
2
17
29
44
37
45
17
49
2
(10 rows)


what i want:



input: column which stores array values say 2000 elements in a single record.



I came across cube extension and postGIS there i can get distance between two points by using tree and distance concepts for lower dimentsions upto 100.




  1. How to find the distance between two arrays having elements atleast 2000 in postgresql?

  2. which tree is best for 2000 dimension indexing in postgresql?

  3. finally i want to know how to use KNN search in postgresql?










share|improve this question
















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    1















    What I did:




    1. installed postgresql 9.3.1

    2. installed postgis 2.1.2

    3. I tried to find the distance by selecting column input_variable_1 with value 50.


    I got the following result.



    select input_variable_1 <-> 50  as distance  from test_ata limit 10;
    distance
    48
    2
    17
    29
    44
    37
    45
    17
    49
    2
    (10 rows)


    what i want:



    input: column which stores array values say 2000 elements in a single record.



    I came across cube extension and postGIS there i can get distance between two points by using tree and distance concepts for lower dimentsions upto 100.




    1. How to find the distance between two arrays having elements atleast 2000 in postgresql?

    2. which tree is best for 2000 dimension indexing in postgresql?

    3. finally i want to know how to use KNN search in postgresql?










    share|improve this question
















    bumped to the homepage by Community 1 min ago


    This question has answers that may be good or bad; the system has marked it active so that they can be reviewed.


















      1












      1








      1








      What I did:




      1. installed postgresql 9.3.1

      2. installed postgis 2.1.2

      3. I tried to find the distance by selecting column input_variable_1 with value 50.


      I got the following result.



      select input_variable_1 <-> 50  as distance  from test_ata limit 10;
      distance
      48
      2
      17
      29
      44
      37
      45
      17
      49
      2
      (10 rows)


      what i want:



      input: column which stores array values say 2000 elements in a single record.



      I came across cube extension and postGIS there i can get distance between two points by using tree and distance concepts for lower dimentsions upto 100.




      1. How to find the distance between two arrays having elements atleast 2000 in postgresql?

      2. which tree is best for 2000 dimension indexing in postgresql?

      3. finally i want to know how to use KNN search in postgresql?










      share|improve this question
















      What I did:




      1. installed postgresql 9.3.1

      2. installed postgis 2.1.2

      3. I tried to find the distance by selecting column input_variable_1 with value 50.


      I got the following result.



      select input_variable_1 <-> 50  as distance  from test_ata limit 10;
      distance
      48
      2
      17
      29
      44
      37
      45
      17
      49
      2
      (10 rows)


      what i want:



      input: column which stores array values say 2000 elements in a single record.



      I came across cube extension and postGIS there i can get distance between two points by using tree and distance concepts for lower dimentsions upto 100.




      1. How to find the distance between two arrays having elements atleast 2000 in postgresql?

      2. which tree is best for 2000 dimension indexing in postgresql?

      3. finally i want to know how to use KNN search in postgresql?







      postgresql-9.3 postgis nearest-neighbor






      share|improve this question















      share|improve this question













      share|improve this question




      share|improve this question








      edited Mar 24 '17 at 8:49









      Marco

      3,73231524




      3,73231524










      asked Mar 23 '17 at 14:15









      harishankarharishankar

      61




      61





      bumped to the homepage by Community 1 min ago


      This question has answers that may be good or bad; the system has marked it active so that they can be reviewed.







      bumped to the homepage by Community 1 min ago


      This question has answers that may be good or bad; the system has marked it active so that they can be reviewed.
























          1 Answer
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          You have one option, you can recompile the cube extension to use more than 100 dimensions



          KNN Search is done with PostGIS using the <-> operator on two points. You can find out how to do that in the docs.. It doesn't operate in Nd-space. PostGIS isn't an abstract library for math. It's for real world geospatial problems. KNN in 1d, and 4d+ is not a real world problem, or at least not in the domain that PostGIS would be interested in.



          I would suggest checking out my other answer here,




          • Searching in n-dimensional space






          share|improve this answer


























          • 1.first convert your array into cube(array) 2.apply cube_distance to the converted array 3.apply sorting u may get nearest values

            – harishankar
            Mar 31 '17 at 11:39













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          1 Answer
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          1 Answer
          1






          active

          oldest

          votes









          active

          oldest

          votes






          active

          oldest

          votes









          0














          You have one option, you can recompile the cube extension to use more than 100 dimensions



          KNN Search is done with PostGIS using the <-> operator on two points. You can find out how to do that in the docs.. It doesn't operate in Nd-space. PostGIS isn't an abstract library for math. It's for real world geospatial problems. KNN in 1d, and 4d+ is not a real world problem, or at least not in the domain that PostGIS would be interested in.



          I would suggest checking out my other answer here,




          • Searching in n-dimensional space






          share|improve this answer


























          • 1.first convert your array into cube(array) 2.apply cube_distance to the converted array 3.apply sorting u may get nearest values

            – harishankar
            Mar 31 '17 at 11:39


















          0














          You have one option, you can recompile the cube extension to use more than 100 dimensions



          KNN Search is done with PostGIS using the <-> operator on two points. You can find out how to do that in the docs.. It doesn't operate in Nd-space. PostGIS isn't an abstract library for math. It's for real world geospatial problems. KNN in 1d, and 4d+ is not a real world problem, or at least not in the domain that PostGIS would be interested in.



          I would suggest checking out my other answer here,




          • Searching in n-dimensional space






          share|improve this answer


























          • 1.first convert your array into cube(array) 2.apply cube_distance to the converted array 3.apply sorting u may get nearest values

            – harishankar
            Mar 31 '17 at 11:39
















          0












          0








          0







          You have one option, you can recompile the cube extension to use more than 100 dimensions



          KNN Search is done with PostGIS using the <-> operator on two points. You can find out how to do that in the docs.. It doesn't operate in Nd-space. PostGIS isn't an abstract library for math. It's for real world geospatial problems. KNN in 1d, and 4d+ is not a real world problem, or at least not in the domain that PostGIS would be interested in.



          I would suggest checking out my other answer here,




          • Searching in n-dimensional space






          share|improve this answer















          You have one option, you can recompile the cube extension to use more than 100 dimensions



          KNN Search is done with PostGIS using the <-> operator on two points. You can find out how to do that in the docs.. It doesn't operate in Nd-space. PostGIS isn't an abstract library for math. It's for real world geospatial problems. KNN in 1d, and 4d+ is not a real world problem, or at least not in the domain that PostGIS would be interested in.



          I would suggest checking out my other answer here,




          • Searching in n-dimensional space







          share|improve this answer














          share|improve this answer



          share|improve this answer








          edited Apr 13 '17 at 12:42









          Community

          1




          1










          answered Mar 23 '17 at 17:08









          Evan CarrollEvan Carroll

          32k969219




          32k969219













          • 1.first convert your array into cube(array) 2.apply cube_distance to the converted array 3.apply sorting u may get nearest values

            – harishankar
            Mar 31 '17 at 11:39





















          • 1.first convert your array into cube(array) 2.apply cube_distance to the converted array 3.apply sorting u may get nearest values

            – harishankar
            Mar 31 '17 at 11:39



















          1.first convert your array into cube(array) 2.apply cube_distance to the converted array 3.apply sorting u may get nearest values

          – harishankar
          Mar 31 '17 at 11:39







          1.first convert your array into cube(array) 2.apply cube_distance to the converted array 3.apply sorting u may get nearest values

          – harishankar
          Mar 31 '17 at 11:39




















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